"""
============
Seam Carving
============

This example demonstrates how images can be resized using seam carving [1]_.
Resizing often distorts contents in the image. Seam carving tries to resize
images while trying to keep important content intact. In this example we are
using the Sobel filter to signify the importance of each pixel.

.. [1] Shai Avidan and Ariel Shamir
       "Seam Carving for Content-Aware Image Resizing"
       http://www.cs.jhu.edu/~misha/ReadingSeminar/Papers/Avidan07.pdf

"""
from skimage import data, draw
from skimage import transform, util
import numpy as np
from skimage import filters, color
from matplotlib import pyplot as plt


hl_color = np.array([0, 1, 0])

img = data.rocket()
img = util.img_as_float(img)
eimg = filters.sobel(color.rgb2gray(img))

plt.title('Original Image')
plt.imshow(img)

"""
.. image:: PLOT2RST.current_figure
"""

resized = transform.resize(img, (img.shape[0], img.shape[1] - 200))
plt.figure()
plt.title('Resized Image')
plt.imshow(resized)


"""
.. image:: PLOT2RST.current_figure
"""

out = transform.seam_carve(img, eimg, 'vertical', 200)
plt.figure()
plt.title('Resized using Seam-Carving')
plt.imshow(out)

"""
.. image:: PLOT2RST.current_figure

As you can see, resizing as distorted the rocket and the objects around,
whereas seam carving has reszied by removing the empty spaces in between.

Object Removal
--------------

Seam Carving can also be used to remove atrifacts from images. To do that, we
have to ensure that pixels to be removes get less importance. In the following
code I approximately mark the rocket with a mask, and then decrease the
importance of those pixels

"""

masked_img = img.copy()

poly = [(404, 281), (404, 360), (359, 364), (338, 337), (145, 337), (120, 322),
        (145, 304), (340, 306), (362, 284)]
pr = np.array([p[0] for p in poly])
pc = np.array([p[1] for p in poly])
rr, cc = draw.polygon(pr, pc)

masked_img[rr, cc, :] = masked_img[rr, cc, :]*0.5 + hl_color*.5
plt.figure()
plt.title('Object Marked')

plt.imshow(masked_img)
"""
.. image:: PLOT2RST.current_figure
"""

eimg[rr, cc] -= 1000

plt.figure()
plt.title('Object Removed')
out = transform.seam_carve(img, eimg, 'vertical', 90)
resized = transform.resize(img, out.shape)
plt.imshow(out)
plt.show()
"""
.. image:: PLOT2RST.current_figure
"""